Analysis of Histogram and Grayscale on Chest X-Ray in Lung Cancer Using Image-J

Abstract

Posteranterior (PA) chest radiographic examination is a support in screening for the diagnosis of lung cancer. Computed radiography (CR) modality can produce chest images quickly, optimally and can be processed as needed. However, so far radiologists interpret images only by visual assessment, so the results are very subjective. Therefore digital medical image processing can be done by looking at the histogram and gray scale values to increase the accuracy of enforcing patient diagnoses. This study aims to analyze the comparison of histograms and gray degree values on CR chest images between normal patients and lung cancer patients. The study was conducted using 30 chest images consisting of normal and lung cancer patient groups with 15 images each. All images are calculated grayscale and display histogram graphics with the Image-J application and statistically analyzed using the Independent T-Test. The results show that there is a difference in grayscale values between normal chest images and lung cancer (p<0.001). The grayscale and histogram values on lung cancer chest images ( 103.2908 + 6.119 ) are higher and tend to the right compared to the grayscale and histogram values on normal chest images ( 64.5848 + 3.28) . Histogram and grayscale values add objective image interpretation in diagnosing lung cancer.